The increasing amount of digital media available on local storage devices and interconnected storage devices and networked servers gives rise to the need of managing such media by means of various technologies together referred to as Digital asset management (DAM). Digital asset management consists of management tasks and decisions surrounding the ingestion, annotation, cataloguing, storage, retrieval and distribution of digital assets. A sub-category of Digital asset management called Media Asset Management (MAM) deals with assets or contents such as digital photographs, animations, videos and music.
Tracking content across a Media Asset Management (MAM) workflow have become an integral part of workflow management to take decisions like determining the content that needs to undergo a quality verification, resizing the resolution from HD to SD for digital television, frame rate change as per NTSC or PAL standard, inserting advertisements between movies, removing unwanted shots/scenes, and the like. The digital content stored in terms of files are subjected to various kinds of operations for broadcasting to various regions and through various channels like digital television, web delivery, mobile etc. These operations are done in various workflow stages.
Due to the vast amount of information available, processes for identifying similar videos may be desirable. Given the large quantity of videos that may be made available on various web sites, it may be desirable for web site operators to be able to identify if one or more video files correspond to one or more other video files. Hence there is a need to develop a video fingerprinting technique through which media files can be linked after undergoing these transformations. Media files with similar fingerprints contain portions of same video.
A video fingerprint is a compact digital representation of a video that summarizes the unique characteristics of the video. The fingerprint data file of a video can be stored, retrieved and used to identify the original video whenever required. Video fingerprinting generates a unique digital profile and can be used to analyze and identify any video source such as TV, video repositories, other digital streams, and the like. A Video fingerprint is useful for tracking or searching similar content that may accessed for Media Asset Management. A video fingerprint may also be useful to identify copyright violation or copyright monetization in a system having user generated content. For example, in a system where a user can upload a video, video fingerprinting may be useful to identify situations where there has been a violation of a third party's copyright with the uploaded video. If a user has improperly incorporated a copyrighted work into uploaded video, a video fingerprint may help to identify the source of the copyrighted video, which may help in disabling access to user video that improperly incorporates the copyrighted video. In addition, video fingerprinting may be useful for detecting copyrighted works for other purposes, such as for tracking and distributing royalties for licensed works. In addition, video fingerprinting may be useful for identifying duplicate content. In this example, video files may, under some circumstances involve significant amounts of storage. At least in part by reducing duplicate content a system or process may be able to improve performance or cost by reducing the amount of storage for saved content. In addition, video fingerprinting may be useful in improving video search engine results, for example, such as by presenting more relevant searches earlier or by identifying alternate copies of video content. Furthermore, search results with similar video fingerprints may be grouped together for presentation to a searcher.
Video fingerprinting is based on the unique characteristics of the video and can be used to compare similar videos. Different versions of the same video may have different fingerprints and may be used to identify and classify different but related versions. Similar content for a given query is searched in a database storing a plurality of fingerprints. A digital video comprises of one or more shots. The fingerprint of a video is determined based on the shot transition frames present in a video that are in turn detected based on the shot boundaries present in a video. A technique known as Locality Sensitive Hashing (LSH) is applied on shots' duration and obtained buckets are stored in database for long duration videos like serials or movies.
Identifying the shots in video require frame by frame analysis of all the frames present in a video and fingerprint computed by this means is called regular fingerprint. Since shot identification is a time consuming process and may delay critical decisions with respect to a video, hence, there exists a need for a faster version of fingerprint extraction which tries to identify shots by identifying and analyzing only a few selected frames amongst a plurality of frames present in the video.